Below is a selection of dissertations from the Doctor of Philosophy in Computational and Data Sciences program in Schmid College that have been included in Chapman University Digital Commons. Additional dissertations from years prior to 2019 are available through the Leatherby Libraries' print collection or in Proquest's Dissertations and Theses database.

If you are a previous student and would like to include your dissertation in Chapman University Digital Commons, please contact Kristin Laughtin-Dunker at laughtin@chapman.edu.

Follow

Dissertations from 2020

PDF

A Computational and Experimental Examination of the FCC Incentive Auction, Logan Gantner

PDF

Exploring the Employment Landscape for Individuals with Autism Spectrum Disorders using Supervised and Unsupervised Machine Learning, Kayleigh Hyde

PDF

Integrated Machine Learning and Bioinformatics Approaches for Prediction of Cancer-Driving Gene Mutations, Oluyemi Odeyemi

PDF

On Quantum Effects of Vector Potentials and Generalizations of Functional Analysis, Ismael L. Paiva

PDF

Long Term Ground Based Precipitation Data Analysis: Spatial and Temporal Variability, Luciano Rodriguez

PDF

Connecting the Dots for People with Autism: A Data-driven Approach to Designing and Evaluating a Global Filter, Viseth Sean

PDF

Novel Statistical and Machine Learning Methods for the Forecasting and Analysis of Major League Baseball Player Performance, Christopher Watkins

Dissertations from 2019

PDF

Contributions to Variable Selection in Complexly Sampled Case-control Models, Epidemiology of 72-hour Emergency Department Readmission, and Out-of-site Migration Rate Estimation Using Pseudo-tagged Longitudinal Data, Kyle Anderson

PDF

Bias Reduction in Machine Learning Classifiers for Spatiotemporal Analysis of Coral Reefs using Remote Sensing Images, Justin J. Gapper

PDF

Estimating Auction Equilibria using Individual Evolutionary Learning, Kevin James

PDF

Employing Earth Observations and Artificial Intelligence to Address Key Global Environmental Challenges in Service of the SDGs, Wenzhao Li

PDF

Image Restoration using Automatic Damaged Regions Detection and Machine Learning-Based Inpainting Technique, Chloe Martin-King

Theses from 2017

PDF

Optimized Forecasting of Dominant U.S. Stock Market Equities Using Univariate and Multivariate Time Series Analysis Methods, Michael Schwartz